Maximilian Teltzrow

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Personalized (or “user-adaptive”) systems have gained substantial momentum with the rise of the World Wide Web. The market research firm Jupiter (Foster, 2000) defines personalization as predictive analysis of consumer data used to adapt targeted media, advertising and merchandising to consumer needs. According to Jupiter, personalization can be viewed as a(More)
Numerous studies have demonstrated the effectiveness of personalization using quality criteria both from machine learning / data mining and from user studies. However, a site requires more than a high-performance personalization algorithm: it needs to convince its users to input the data needed by the algorithm. Today’s Web users are becoming increasingly(More)
Consumer surveys demonstrated that privacy statements on the web are ineffective in alleviating users’ privacy concerns. We propose a new user interface design approach in which the privacy practices of a website are explicated in a contextualized manner, and users’ benefits in providing personal data clearly explained. To test the merits of this approach,(More)
Sophisticated Data Mining tools are able to provide valuable information for online retailers. But especially when an external data mining service provider is contracted, important questions arise concerning the privacy preservation of the shop customers. This paper discusses the specific case of an online retailer who aims at usefully analysing customers’(More)
The analysis of consumer-related and consumer-generated data for measuring the success of online retailing is gaining increasing importance. Software packages for data analysis have become commonplace. However, two major shortcomings exist. First, most software solutions are not offered as a service reachable by standard procedures over the Internet, but as(More)